package com.tangpian.sna.core.analysis.lda.algorithm;

import java.io.Serializable;

public class LDAOption implements Serializable {

	private static final long serialVersionUID = 526166310343530738L;
	public static final long BUFFER_SIZE_LONG = 1000000;
	public static final short BUFFER_SIZE_SHORT = 512;

	public static final int MODEL_STATUS_UNKNOWN = 0;
	public static final int MODEL_STATUS_EST = 1;
	public static final int MODEL_STATUS_ESTC = 2;
	public static final int MODEL_STATUS_INF = 3;
	// Specify whether we want to estimate model from scratch
	public boolean est = false; // //

	// Specify whether we want to continue the last estimation
	public boolean estc = false; // /

	// Specify whether we want to do inference
	public boolean inf = true; // //

	public String dir = ""; // Specify directory ////
	public String dfile = ""; // Specify resource data filename ////

	// Specify the model level to which you want to applied. ///
	public String modelName = ""; // /

	public int K = 10; // Specify the number of topics ///

	public double alpha = 0.5; // Specify alpha ////
	public double beta = 0.02; // Specify beta

	public int niters = 1000; // Specify the number of iterations //

	// Specify the number of steps to save the model since the last save.
	// The step (counted by the number of Gibbs sampling iterations)
	// at which the LDA model is saved to hard disk.
	public int savestep = 200;

	// Specify the number of most likely words to be printed for each topic
	public int twords = 30; // /

	// Specify whether we include raw data in the input
	public boolean withrawdata = false;

	// Specify the wordmap file
	public String wordMapFileName = "wordmap.txt"; // //

	public static String chartSet = "utf-8";
}
